Current commercially available manufacturing execution system (MES) packages are used throughout the semiconductor manufacturing sector. These systems track each wafer and determine where it has been and where the wafer needs to go. However, the model of statistical process control (SPC) employed by most commercially available packages is a naive model with assumptions built into the system that are incorrect, i.e., one parameter is measured, at one place, using only one type of product, only once. For example, most SPC systems are entity- and lot-based, but the real world of the factory is chamber- and wafer-based. From an automation user's point of view, these SPC systems are difficult for programmers to maintain and enhance. Also, at least in part because of the assumptions, these SPC systems require many statistical process control charts (over 14,000 for a typical fab operation) for effective process monitoring. Maintaining so many charts is costly, hinders change, and can obscure important statistics. In addition, due to the monolithic nature of charting systems used with current semiconductor SPC systems, producing a statistical process control chart for viewing is typically a labor-intensive process.
Individual point solutions offered by various vendors for particular applications do not adequately address the shortcomings of currently available systems, because point solutions do not take into account the many different databases and manufacturing models, with their attendant integration problems. Hence, the use of many independent point solutions may generate communications barriers caused by multiple point solutions not being easily integratable within the larger whole of an MES system.
Accordingly, a need exists for a solution to the problems currently encountered with the statistical process control and disparate database collection aspects of manufacturing execution systems in semiconductor manufacturing facilities.